Summary: Laser-capture microdissection (LCM), invented by Dr. Lance Liotta at the NCI, has enabled researchers for the first time to be able to analyze purified populations of cells directly from pateint tissue samples. These popluations include, but are not limited to, cancer epithelial cells- cells which comprise only 1-2% of the total population of cells found in any non-hematopoetic dervied tumor (the rest being stromal cells, fibroblasts, infiltrating lymphocytes, etc.). In a close collaborative effort, I have become the lead investigator for the proteomic analysis of cancer cells from a variety of tissue types (prostate, breast, lung, esophogeal, lung, brain, ovary, colon) derived from laser-capture microdissected cells. These cells have been analysed via 2D-PAGE protein fingerprinting, signal pathway profiling, phophoprotein analysis, SELDI protein chip retentate mapping anlysis, multiplexed scanning immunoblot analysis. Additionally, serum and body fluid tumor marker identification is being performed via SELDI and 2D-PAGE analysis. We have found that we can successfully recover and analyze proteins from the LCM and have identified over one hundred proteins from ovarain, breast, lung, colon, prostate and esophogeal cancer that are differentially regulated (turned off or turned on). Over 150 proteins have been identified so far that track with the malignant phenotype. We are validating these now using a novel tool we have invented using high-throuput microarray-based lysates, antibdy arrays, and phosphoprotein pattern profiling. We have now taken these tools and are implementing them in actual human clinical trials for the first time ever. We have developed tools usign laser capture microdissection technology to analyze the signaling pathways of cells form biopsy before during and after therapeutics in ongoing human clinical trials at the NCI. We have succesfully employed SELDI and phosphoprotein capture analysis on LCM derived cells , and invented a novel artifical intelligence-based algorithm for diagnostic analysis of cancer from SELDI-derived protein patterns using body fluids or LCM-procured cellular lysates. We have found that we can discriminate with 100% sensitivity and 100% specificity prostate cacner from serum, irrespective of PSA values. We are currently using this approach to analyze serum from ovarain cancer patients and found we can detect early stage cancer nearly 100% of the time.